The anatomical structure of hardwood is inherently three-dimensional (3D), whereas conventional two-dimensional (2D) section-based analyses are limited in accurately quantifying structural dimensions and tissue proportions. To evaluate the applicability of 2D and 3D approaches for quantitative hardwood anatomical analysis, this study combines traditional 2D microscopy with X-ray micro-computed tomography (X-ray-µCT) to achieve 3D visualization and quantitative characterization of major anatomical features in representative hardwood species. Eleven hardwood species were investigated, and internal 3D structural information was obtained under optimized scanning and reconstruction conditions. Using Acer truncatum as a reference species, vessel and fiber diameters measured from 2D sections showed strong agreement with corresponding 3D X-ray-µCT measurements (R² > 0.90, slopes close to 1), confirming the accuracy of X-ray-µCT at the cellular scale. In contrast, clear differences were observed in tissue fraction estimates. Three-dimensional analyses revealed vessel volume fractions of 19–24
Fluctuations in indoor humidity can negatively affect the comfort and health of occupants while contributing to the deterioration of building materials. Although biochar has been widely studied as a porous carbon material, its application in humidity regulation has received limited attention. Moreover, no previous study has reported the grafting of biochar with 3-aminopropyltriethoxysilane (APTES) for the synthesis of humidity-regulating building materials. In this study, biochar produced by carbonizing waste tree branches at 800 °C underwent surface-grafting with APTES through a reflux process. The physicochemical properties of the biochar samples were characterized using Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), Brunauer-Emmett-Teller (BET) analysis, scanning electron microscopy (SEM), and water contact angle measurements. Moisture-regulation performance was evaluated using standardized adsorption and desorption tests. BET analysis indicated the coexistence of microporous and mesoporous structures, corresponding to Type I and Type IV adsorption isotherms. SEM observations revealed irregular particles with flocculent deposits on the biochar surface. FTIR spectra detected characteristic N–H and Si–O–Si bands, confirming the introduction of amino-containing functional groups, while TGA results further supported the presence of grafted APTES. APTES modification reduced the water contact angle to below 90°, indicating increased hydrophilicity. Under cyclic humidity conditions of 33–75
The sustainable conversion of forestry by-products into bioactive biopolymer materials is a promising strategy for biodegradable wound dressing systems. This study valorized Pinus brutia bark extract (PBBE) and resin extract (PBRE) by incorporating them into chitosan-, chitosan/gelatin-, poly(vinyl alcohol) (PVA)/chitosan-, and PVA/starch-based hydrogel films. The extracts were characterized by high-performance liquid chromatography with diode-array detection (HPLC-DAD) and gas chromatography–mass spectrometry (GC-MS), and the films were evaluated for physicochemical properties, release behavior, biological activities, cytotoxicity, and scratch wound closure. PBBE showed a taxifolin-rich phenolic profile, with taxifolin as the major compound (180.5 mg/g), strong 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity (IC50: 7.33 µg/mL), and tyrosinase inhibition comparable to kojic acid. PBRE was dominated by diterpenic acids (87.43
This study examines how the amount of retained metal influences the thermal degradation behaviour of oak wood treated with inorganic salts. After controlled impregnation and removal of loosely bound fractions, metal uptake was quantified by atomic absorption spectroscopy and related to changes in degradation behaviour observed by evolved gas analysis–mass spectrometry and pyrolysis–gas chromatography/mass spectrometry. Clear differences were observed between the various salt treatments. Calcium-based systems showed the highest metal retention and were associated with increased thermal stability, whereas alkali metals promoted more pronounced fragmentation of degradation products. Transition metals exhibited intermediate behaviour, reflecting the combined influence of metal-specific interactions and treatment conditions. The pH of the treatment solutions decreased after contact with wood, indicating that chemical changes during impregnation contribute to the observed behaviour. In addition, thermo-hygrometric ageing led to a general increase in degradation temperatures for all samples, while differences between treatments remained evident. These results highlight the combined role of metal retention, cation chemistry, and environmental exposure in controlling the thermal behaviour of salt-treated oak.
Accurate measurement of tree-ring increments on rough wood surfaces in the field is essential for evaluating forest productivity and merchantability. Conventional imaging approaches are hindered by intensity non-uniformity across the cross-section, particularly between the darker heartwood in the central region and the lighter sapwood towards the periphery. This study presents a spectral imaging method designed to compensate for intensity non-uniformity across the wood cross-section. By equalizing intensity variations between heartwood and sapwood regions, the method enables reliable identification of annual growth rings on unprocessed, rough surfaces of Japanese cedar. The spectral imaging station and the procedure for acquiring spectral images are described. Spectral characteristics that enhance ring visibility are analysed, and an algorithm is proposed for selecting the optimal spectral range to maximise contrast in the intensity-balanced image. The method was applied to 20 rough-surfaced Japanese cedar samples imaged at a spatial resolution of 0.05 mm/pixel. Annual ring increments were successfully quantified on these samples. Although validation on a larger and more diverse set of samples is required to confirm robustness and versatility, the key contribution lies in the proposed spectral imaging technique, which effectively addresses intensity non-uniformity and enables reliable dendrometric measurements on challenging field samples.
Wood specimens preserved in xylaria are valuable genetic resources, but their highly fragmented and degraded DNA poses major challenges for genomic studies. This research established a feasible xylarium genomics approach by applying hybridization capture combined with next-generation sequencing to archived Fraxinus specimens, successfully retrieving high-quality plastid genomes with 99.89–100
Freezing can notably alter the cutting behaviour of wood, yet quantifying its influence is challenging due to variability in wood properties and the interplay of factors such as moisture content (MC), temperature and density. This study uses a tightly controlled design to isolate the effect of freezing on cutting forces of Scots pine (Pinus sylvestris L.) in green state. Heartwood and sapwood were analysed separately due to their distinct MC, at four temperature levels: -20 ^∘ C, -10 ^∘ C, 0 ^∘ C, and 22 ^∘ C. A data-driven machine-learning approach, combined with SHAP analysis and partial dependence plots, was used to identify and interpret the most influential variables on main cutting force. Results show that heartwood at 30 0 and -10 ^∘ C as free water freezes. This phase change alters the cutting mechanism, reducing friction but increasing resistance when cutting through ice and the ice–wood composite, with the net effect depending on uncut chip thickness. These findings provide mechanistic insight into temperature-dependent cutting behaviour and inform optimisation of sawing strategies for frozen logs in industrial practice.
Radial stem growth in trees and shrubs is a fundamental process influencing their development and adaptation. Traditionally, radial growth has been attributed primarily to the radial expansion of cambial cells and their derivatives. In this study, we investigated the contributions of both the tips and bodies of wood fibers to radial growth in black locust. An anatomical and statistical approach was applied to the analysis of collected plant tissues, including the vascular cambium and secondary xylem, which were prepared using a Tesla ultramicrotome. Our study indicated that, beyond commonly recognized radial enlargement of cells associated with cell wall growth, secondary xylem radial enlargement within black locust is also driven by fiber development in two distinct ways: (1) axial intrusive growth coupled with transverse expansion of wood fiber tips, and (2) shape transformation of developing fiber bodies in the transverse plane, from rectangular to more circular forms. We hypothesize that this mechanism may provide an adaptive advantage by optimizing resource allocation while maintaining mechanical stability, since transverse enlargement of fiber bodies appears to occur without substantial structural carbon investment prior to secondary cell wall deposition. These findings offer a novel developmental perspective on wood formation in black locust by challenging the classical paradigm of symplastic growth in the secondary xylem differentiation zone. These new insights may have implications for optimizing wood production and for advancing our fundamental understanding of developmental mechanisms in angiosperm woody plants.
This study proposes an original methodology for the online measurement of local moisture content (MC) in poplar veneer, combining colour imaging and laser scattering techniques. A database of poplar samples was built, including colour images and a grid of scattering patterns caused by the tracheid effect, acquired in both reflection and transmission modes. The analysis shows that colour becomes a discriminant parameter as MC increases. However, colour information alone proved insufficient for accurate MC prediction. The model shows limited performance at low moisture contents, with a coefficient of determination R² of 0.857 and an absolute error exceeding 100
In this study, bark waste from the forest industry derived from Pinus sylvestris was processed by pyrolysis extraction, and the chemical compositions and biological activities of the resulting light (PLF) and heavy (PHF) fractions were comparatively investigated. When the extraction yields of the pyrolysis fractions were compared, PHF (20.80
Elastic modulus reflects the ability of wood to resist deformation. The existing longitudinal vibration method plays an important role in the determination of elastic modulus of wood. To simplify the detection system and facilitate measurement, a novel method for measuring the elastic modulus of wood has been proposed, utilizing the longitudinal vibration excitation and electromechanical admittance (EMA) response of dual lead zirconate titanate (PZT) patches coupled with the specimen. To verify the effectiveness of the proposed method, theoretical derivation, finite element simulation and experimental research were carried out respectively. The theoretical derivation results show that the first-order longitudinal vibration mode frequency of the beam specimen coupled with dual PZT patches can be extracted through the real part of EMA response. Simulation results of six kinds of wood specimens show that the dual PZT patch transducer can effectively excite the first-order longitudinal vibration mode of the specimen, the main peak that corresponds to the first-order longitudinal vibration mode of the specimen exists in the EMA response, and the relative errors of the measurement results are less than 0.35
Monitoring the lignin content in pulpwood is essential for timely adjustments of the pulping process and optimization of process parameters. Near-infrared (NIR) spectroscopy, as a fast and non-destructive technique, provides an important means to detect the chemical composition of pulpwood. As benchtop and handheld NIR spectrometers become more widely used, the ability to share analytical models between them would significantly reduce the cost and time required for model development and increase the efficiency of model application. In this study, a benchtop spectrometer (S450) and a handheld spectrometer (NeoSpectra) were utilized to collect NIR spectral data on a total of 174 pulpwood samples, respectively. Based on the lignin content of the pulpwood samples and their near-infrared spectra collected on the two spectrometers, four methods, namely, partial least squares regression (PLSR), support vector regression (SVR), random forest (RF), and long short-term memory (LSTM), were used to build the hybrid models, and the predictive and sharing performances of the models were compared and analyzed. To further optimize the models and enhance their accuracy, feature wavelength selection strategies, such as elimination of uninformative variables (UVE) and competitive adaptive reweighted sampling (CARS), were employed to improve the models. The results showed that the hybrid model incorporating the UVE-LSTM approach performed the highest sharing capability, with coefficient of determination (R2) values of 0.99 and 0.92 on the benchtop and handheld spectrometers, respectively. Therefore, a hybrid calibration approach, which combines deep learning algorithms with suitable wavelength selection techniques, significantly boosts the model’s robustness and generalization ability and successfully achieves the best performance on benchtop and handheld NIR spectrometers for model sharing of lignin content in pulpwood.
Short-rotation plantation hardwoods are increasingly used to meet timber demand but are often harvested before optimal structural properties are achieved. This limits their suitability for high-value timber applications. Improving the mechanical properties of young trees through selective breeding is a viable strategy, particularly when supported by molecular tools. However, limited information exists on how genetic and phenotypic variation influence structural traits across the stem profile. This study assessed variation in the mechanical properties of Eucalyptus pellita and its hybrids to support breeding for structural timber. Modulus of elasticity (MOE), modulus of rupture (MOR), and compressive strength (CS) were measured in inner and outer wood across multiple stem heights. These traits were correlated with physical properties, growth, and chemical traits. A single nucleotide polymorphism (SNP)-based genetic association analysis was also conducted. Outer wood and middle stem positions showed the highest values, with MOE up to 17,700 MPa, MOR up to 147 MPa, and CS up to 70 MPa, particularly in the E. pellita × E. brassiana hybrid. Mechanical traits correlated positively with height and diameter at breast height, while microfibril angle was negatively associated with CS (r = − 0.30 inner; − 0.24 outer). Lignin content showed positive associations with MOR and CS. SNP-based genetic analysis identified loci linked to MOE and MOR, including SNP4096 near Eucgr.A00211, a candidate gene potentially involved in cell wall regulation and wood strength. These findings highlight the potential of combining phenotypic and genomic tools to improve the selection of fast-grown hardwoods for high-value structural applications.
Atomic Force Microscopy in PeakForce Quantitative NanoMechanics mode (AFM PeakForce QNM) under controlled relative humidity (RH) was applied to continuously monitor the indentation modulus (IM) of Norway spruce (Picea abies) earlywood (EW) and latewood (LW) tracheid cell walls over three absorption/desorption (S/D) cycles. The IM of the different cell wall layers were close between early- and latewoods indicating small differences between their chemical compositions. AFM nanoInfraRed measurements (AFM NanoIR) indicate variations in lignin and cellulose with an increase of lignin and a decrease of cellulose from the S2 to the S1 and finally to the CC (cell corner). Earlywood and latewood cell walls display the same hygronanomechanical behavior during S/D cycle, i.e., the IM values decrease during absorption up to 85
To elucidate the influence of wood fiber size distribution and resin content on the elastic constitutive behavior of high-density fiberboard (HDF), a transversely isotropic constitutive model was used based on the mat-forming and hot-pressing processes and the characteristic density profile of HDF. Displacement fields under three-point bending were obtained experimentally using digital image correlation (DIC), analytically from Timoshenko beam theory, and numerically through finite element model updating (FEMU). These displacement fields were integrated to identify five independent elastic constitutive parameters— transverse elastic modulus, longitudinal elastic modulus, longitudinal shear modulus, transverse Poisson's ratio, and longitudinal Poisson's ratio—by means of nonlinear least-squares optimization. The identified parameters were compared among HDF specimens manufactured with different wood fiber size distributions and resin contents. Furthermore, the microscopic fracture morphologies of bending failure surfaces were analyzed to clarify the underlying mechanisms by which fiber size distribution and resin content affect the mechanical performance of HDF. The results demonstrate that the mechanical properties of HDF exhibit pronounced directional dependence, which is governed by fiber interweaving, fiber–resin interfacial bonding, and internal pore defects. Fine fibers fill internal pores and reduce structural defects, while medium and long fibers form the primary load-bearing framework. Excessive coarse fibers hinder fiber interlocking and promote pore formation, degrading mechanical performance. Increasing resin content enhances interfacial bonding, thereby improving static bending strength and elastic moduli. This study provides a methodological reference for characterizing the parameters of wood-based materials such as HDF.
The heat of sorption ( Q_L ) of four high extractive content woods—western red cedar, Chinese juniper, tubi and messmate—were determined using an isosteric approach based on previously collected water sorption isotherm data at 30, 45, 60, 75, 90 and 99.5 ℃. The isotherm data at every single temperature ( T ) was fitted using the Hailwood-Horrobin (HH) model. The resulting Q_L versus moisture content ( M ) plot displays a characteristic peak in the low M region. This peak is sensitive to the sorption data selected and can be complicated by overfitting of the HH model. In contrast, when sorption data from all T levels were fitted using the multi-temperature Heikkilä model, the predicted Q_L versus M curves closely aligned with findings obtained from the calorimetric method. The Heikkilä model suggests that Q_L varies with T throughout the entire hygroscopic range and specifically decreases with increasing T . Other multi-temperature models being evaluated, including the Chung-Pfost, Day-Nelson and Zuritz models, were less reliable in predicting Q_L values and their dependence on T . Both the HH and Heikkilä models indicate that as M approaches zero, the Q_L values for untreated samples are higher than those for extracted samples. This suggests that the adsorbed water molecules can disrupt the weak physical interactions between wall polymers and extractive molecules. Consequently, this process can lead to stable or even increased Q_L values if more available sorption sites are exposed in the swollen cell walls due to the deposition of extractives.
Densified wood (DW) is a promising sustainable structural material with excellent mechanical performance, whose fire safety can be significantly enhanced through flame-retardant treatment. However, comprehensive pyrolysis models for flame-retardant densified wood (FRDW) remain limited. In this study, ammonium dihydrogen phosphate (ADP)-impregnated densified wood (DW-ADP) was prepared and its pyrolysis and combustion behaviors were investigated through experiments and numerical simulations. Compared with untreated DW, DW-ADP exhibited lower pyrolysis temperatures, increased char yield, delayed ignition, and reduced heat release due to the catalytic effect of ADP. Pyrolysis models for DW, ADP, and DW-ADP were developed via inverse analysis and parameter optimization using microscale characterization data. Initial DW-ADP models based on either parallel integration of DW and ADP reactions scheme or full seven-step consecutive reaction scheme reproduced microscale characterization curves but failed to predict combustion characteristics. A modified ‘1 + 6’ reaction scheme, incorporating an extractive pyrolysis reaction in parallel with six consecutive reactions, was therefore proposed. This model accurately reproduced experimental combustion behavior, with prediction uncertainties below 20
Wood is a naturally porous material that is highly susceptible to fungal degradation, which significantly limits its practical applications. In this study, carbon quantum dots (CQDs) were in-situ synthesized in wood substrates through a urea pretreatment with concentrations of 4, 8, 12, 16, 20
CT scans offer a valuable way to automatically segment knots, however wet logs pose a crucial challenge for sawmills, due to the similar intensity between water saturated sapwood and the knot. Most existing approaches rely on traditional segmentation techniques or 2D surface level imaging limiting their effectiveness for internal knot characterisation. To address this, we propose a 3D segmentation model tailored specifically for Norway spruce knots, using a comprehensive dataset of 24 trees from three different regions of Sweden (384 CT volumes). We systematically benchmarked popular state of the art 3D deep learning architectures used in medical image segmentation utilising the MONAI framework. Our new model KnotSegNet3D combines residual blocks in both encoder and decoder for improved boundary delineation. The models were evaluated using wet stem sections, reflecting sawmill conditions, while training involved a mixture of training on dry and wet data along with transfer learning from dry to wet. Mixed training achieved the highest accuracy (Dice: 0.902±0.025 ) and the closest boundaries (HD95: 1.610±0.190 mm), higher than the strongest baseline Attention UNet model (Dice: 0.786±0.115 ; HD95: 6.57±12.47 mm), despite having fewer parameters in KnotSegNet3D (15.26M vs 23.63M). Transfer learning also showed similar performance: Full fine-tuning reached Dice 0.896±0.029 and HD95 1.620±0.180,mm , close to mixed training ( 0.902±0.025 ; 1.610±0.190,mm ). In addition, partial fine-tuning reduced training time per epoch due to fewer trainable parameters, providing a practical option when computational resources or annotations are limited. Qualitatively, KnotSegNet3D handled complex knot geometries and consistently delivered better precision and stability in terms of performance index and visual results for trees selected from different regions.
Wood is a viscoelastic material whose mechanical behavior depends on its moisture content. Several experimental studies using ultrasonic tests have reported an increase in the real part of Young’s modulus beyond the fiber saturation point (FSP). This finding contradicts results from other studies conducted at lower frequencies where Young’s modulus remains constant beyond the FSP. This apparent contradiction motivated the present work, which investigates the relationship between wood viscoelasticity and moisture content. First, an enriched experimental protocol was developed to measure the velocity and damping rate of ultrasonic waves in four tropical wood species, allowing to calculate the evolution of Young’s modulus (the real part of the complex viscoelastic modulus) as a function of moisture content. The results of the experimental measurements confirmed trends and values previously reported in the literature: wave velocity and apparent modulus increase above the FSP, highlighting the influence of water content on the dynamic mechanical response of wood. In a second part, a viscoelastic model was proposed to integrate both the evolution of density as a function of moisture content and the dependence of ultrasonic velocity on internal friction. The model reproduced the experimental increase observed in the real part of Young’s modulus above the FSP. This results highlight the importance of accounting for viscoelastic phenomena in wood beyond the FSP.
